There is a saying that goes, “You can’t manage what you can’t measure.” This underlines the need for reports and data points that provide insights into your customers’ experiences and your contact center performance. On the surface that seems fairly straightforward. Within any contact center, there are basic key performance indicators (KPIs) that are measured as a means to gain insight into traffic, efficiency, peak volume, seasonality, and much more.
A standard set of reports and metrics are included as part of their built-in reporting in most contact center tools. And many offer users the ability to pick and choose the specific contents for each report by selecting from the list of available metrics. But BPOs need the ability to see and understand the full picture of the customer journey and contact center operations across data sources and platforms, and the ability to leverage exactly the metrics that measure and show value.
The unique challenges of large enterprises or BPOs
With the added complexity of serving multiple clients or divisions – each with their own unique set of requirements, operational goals, and data sources – the flexibility to report on whatever, whenever, and however can be a huge competitive differentiator. A large enterprise or BPO can gain a competitive advantage by providing not only exceptional contact center service and operational outcomes but also meaningful insight regarding customer experience and contact center performance.
Ask yourself this: are the standard metrics and data points you can select from your toolset able to capture enough insight for meaningful action? Are the pre-defined metrics from the drop-down list adequate given today’s complex cross-channel, cross-platform, holistic customer journey?
What if AHT was unique to you?
Take a look at something seemingly simple as average handle time or AHT. In simplest terms, AHT is a common metric that measures the average length of a call.
AHT is typically calculated using four core metrics:
Total hold time + Total talk time + Any afterwork → all divided by the total number of calls
At first glance this metric may appear sufficient as a performance indicator. At face-value it provides a high-level view of performance at any given point in time, typically when used to compare across other companies in your industry. However, this simplistic approach can be fraught, especially if you’re using it to make operational and business decisions across staffing, performance and validation of your approach to customer service.
What if you could modify the calculation of AHT itself to create a tuned metric that better reflects what you are trying to measure? In essence, changing the formula itself to better reflect what you want to measure.
For instance, if you are a contact center outsourcing company that supports clients in telecommunications and retail, you understand the factors that drive customer satisfaction and churn include first contact resolution, as well as the ability to self-serve. Imagine the value you could bring to your retail clients with the ability to create custom metrics – to tune the calculation of the metric itself to your specific industry and use case needs.
So instead of always using the standard calculation of AHT, it could include (or exclude) IVR transfers for secure credit card transactions for your retail customer; include or exclude transfers between departments when a single call included multiple purposes for your banking customer; or include data from integrations to applications such as Zendesk and Salesforce for your customer in telecom.
The possibilities are endless when you can not only customize your reports, but leverage powerful Business Intelligence to bring data sources together and splice and dice data any way you need. The added specificity and visibility can bring the meaningful insights needed to make critical business decisions and bring operational visibility.
Unify data across the entire customer journey
Featured in 10 use cases, see how Maximus leveraged SuccessKPI to stand up a 20k agent contact center that unified data from Genesys Cloud, a standalone instance of Amazon Connect for attendance tracking, Twilio, Microsoft Dynamics for CRM, Deltek for time recording, Workday for Human Resource and labor management. Each of these tools on their own has reporting, but leveraging SuccessKPI’s business intelligence platform, they were able to unify all the data into one single source of truth, providing incredible insights about operations, performance, and insights into conversations. What began as a data unification and reporting initiative powered by artificial intelligence quickly blossomed into dozens of high-powered use cases applicable to any large enterprise contact center.